In [27]:
#sns.catplot(data=OverallContrsts, x="Contrast", y="logFC", hue="logFC")
fig, ax = plt.subplots(1,1, figsize=(20,15))
sns.axes_style("ticks")
sns.scatterplot(data=OverallContrsts.sort_values(['Contrast','significant']), palette=color_discrete_map,
x="Contrast", y="logFC", size="-logPVal", hue="significant", ax=ax, linewidth=.2,sizes=(100, 700),
edgecolor="black")
sns.lineplot(data=OverallContrsts, x="Contrast", y="logFC",units="genes", estimator=None, alpha=.05, color="grey", ax = ax, zorder=-1)
sns.despine()
ax.legend(bbox_to_anchor=(1.22, 0.8), prop={'size': 30})
# Plot labels
nGenes = 10
# Get pixels size
bbox = ax.get_window_extent().transformed(fig.dpi_scale_trans.inverted())
widthPXL, heightPXL = bbox.width, bbox.height
heightPXL *= fig.dpi
width = 1
height = 1
QuadrantFractionDictH = dict(zip(["Down","notSignificant","Up"],
[1,0,-1]))
offset = lambda p: transforms.ScaledTranslation(p/72.,0, plt.gcf().dpi_scale_trans)
trans = plt.gca().transData
ContrastTuple = (OverallContrsts.loc[OverallContrsts['significant'] != "notSignificant",["Contrast",'significant']].drop_duplicates())
ContrastTuple = list(zip(ContrastTuple.Contrast, ContrastTuple.significant))
for i in ContrastTuple:
PointsText = OverallContrsts[(OverallContrsts["Contrast"] == i[0]) & (OverallContrsts["significant"] == i[1])].sort_values("ABSlogFC", ascending=False).head(nGenes)
PointsText["TextRank"] = (-PointsText["ABSlogFC"]).rank()-1
PointsText["yText"] = [QuadrantFractionDictH[i] for i in PointsText["significant"]]
PointsText["yText"] = PointsText["TextRank"]*PointsText["yText"]
PointsText = PointsText.sort_values("TextRank", ascending=True)
PointsText["FCdelta"] = PointsText["logFC"] - PointsText["logFC"].values[0]
PointsText["yText2"] = PointsText["yText"] - PointsText["FCdelta"]
PointsText["xTextSwitch"] = np.where(PointsText["Contrast"] == "medial_vs_distal",-1,1)
PointsText["xAnchorSwitch"] = np.where(PointsText["Contrast"] == "medial_vs_distal","right","left")
PointsText["xAnchorSwitchArrow"] = np.where(PointsText["Contrast"] == "medial_vs_distal",1,0)
#point["xAnchorSwitch"]
for i, point in PointsText.iterrows():
ax.annotate(str(point['genes']), va="center", ha=point["xAnchorSwitch"],
xy=(point["Contrast"], point['logFC']),
xytext=(200*point["xTextSwitch"], (point["yText2"]*heightPXL/26)),
textcoords='offset points',fontsize=25,
arrowprops=dict(facecolor='black', arrowstyle='-',relpos=(point["xAnchorSwitchArrow"],0.5)))
plt.title("DEGs: {} Qval:{} MinlogFC:{}".format(output_basename.split("_")[1], QTHRESH,LOGCFTHRESHOLD), fontsize=30)
plt.tick_params(axis='both', labelsize=30)
plt.xlabel('Contrast', fontsize=40)
plt.ylabel('logFC', fontsize=40)
fig.savefig("./figures/Volcanos-{}_Qval-{}_MinlogFC-{}.png".format(output_basename.split("_")[1], QTHRESH,LOGCFTHRESHOLD), bbox_inches='tight',dpi = 400)
